Product Images Goyescas 7 Syrups Original Cough And Cold

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The following 2 images provide visual information about the product associated with Goyescas 7 Syrups Original Cough And Cold NDC 11856-0001 by Goyescas Of Fla, such as packaging, labeling, and the appearance of the drug itself. This resource could be helpful for medical professionals, pharmacists, and patients seeking to verify medication information and ensure they have the correct product.

11856-0001 - 7 Jarabes Original 6 Oz 001

11856-0001 - 7 Jarabes Original 6 Oz 001

This is a drug facts label for a cough and cold syrup with three active ingredients - Dextromethorphan HBr (cough suppressant), Guaifenesin (expectorant), and Phenylephrine HCI (nasal decongestant). The syrup helps loosen phlegm and relieves cold and cough symptoms resulting from minor throat and bronchia irritation. It contains alcohol-free ingredients and has relevant warnings, such as not to use with certain drugs, to ask a doctor for cough lasting more than seven days, and to keep out of reach of children. It also has directions for dosages for adults and children over 6 years old. The inactive ingredients include various flavors and sweeteners. The label is distributed by Goyescas Corp in Miami, Florida.*

11856-0001 - 7 Syrups Original Label 6 Oz 001

11856-0001 - 7 Syrups Original Label 6 Oz 001

This is a drug facts label for a cold and cough expectorant and nasal decongestant. It contains dextromethorphan HBr USP 10mg, guaifenesin USP 50 mg, and phenylephrine HCI USP. It helps with nasal congestion and cough due to minor throat and bronchial irritation. It also helps with phlegm and thins bronchial secretions to drain bronchial tubes. It should not be used if you are taking certain drugs for depression. If cough lasts more than 7 days, a doctor should be consulted. The syrup should be dosed as directed by a doctor, and the inactive ingredients include citric acid, sucrose, and caramel color. The product is made by Goyescas USA.*

* The product label images have been analyzed using a combination of traditional computing and machine learning techniques. It should be noted that the descriptions provided may not be entirely accurate as they are experimental in nature. Use the information in this page at your own discretion and risk.